MINLPLib

A Library of Mixed-Integer and Continuous Nonlinear Programming Instances

Home // Instances // Documentation // Download // Statistics


Instance ex9_1_2

Formats ams gms lp mod nl osil pip py
Primal Bounds (infeas ≤ 1e-08)
-16.00000000 p1 ( gdx sol )
(infeas: 4e-16)
Other points (infeas > 1e-08)  
Dual Bounds
-16.00000002 (ANTIGONE)
-16.00000000 (BARON)
-16.00000000 (COUENNE)
-16.00000000 (GUROBI)
-16.00000000 (LINDO)
-16.00000000 (SCIP)
References Floudas, C A, Pardalos, Panos M, Adjiman, C S, Esposito, W R, Gumus, Zeynep H, Harding, S T, Klepeis, John L, Meyer, Clifford A, and Schweiger, C A, Handbook of Test Problems in Local and Global Optimization, Kluwer Academic Publishers, 1999.
Liu, Y H and Hart, S M, Characterizing an Optimal Solution to the Linear Bilevel Programming Problem, European Journal of Operational Research, 79:1, 1994, 164-166.
Source Test Problem ex9.1.2 of Chapter 9 of Floudas e.a. handbook
Added to library 31 Jul 2001
Problem type QCP
#Variables 10
#Binary Variables 0
#Integer Variables 0
#Nonlinear Variables 8
#Nonlinear Binary Variables 0
#Nonlinear Integer Variables 0
Objective Sense min
Objective type linear
Objective curvature linear
#Nonzeros in Objective 2
#Nonlinear Nonzeros in Objective 0
#Constraints 9
#Linear Constraints 5
#Quadratic Constraints 4
#Polynomial Constraints 0
#Signomial Constraints 0
#General Nonlinear Constraints 0
Operands in Gen. Nonlin. Functions  
Constraints curvature indefinite
#Nonzeros in Jacobian 23
#Nonlinear Nonzeros in Jacobian 8
#Nonzeros in (Upper-Left) Hessian of Lagrangian 8
#Nonzeros in Diagonal of Hessian of Lagrangian 0
#Blocks in Hessian of Lagrangian 4
Minimal blocksize in Hessian of Lagrangian 2
Maximal blocksize in Hessian of Lagrangian 2
Average blocksize in Hessian of Lagrangian 2.0
#Semicontinuities 0
#Nonlinear Semicontinuities 0
#SOS type 1 0
#SOS type 2 0
Minimal coefficient 1.0000e+00
Maximal coefficient 4.0000e+00
Infeasibility of initial point 12
Sparsity Jacobian Sparsity of Objective Gradient and Jacobian
Sparsity Hessian of Lagrangian Sparsity of Hessian of Lagrangian

$offlisting
*  
*  Equation counts
*      Total        E        G        L        N        X        C        B
*         10       10        0        0        0        0        0        0
*  
*  Variable counts
*                   x        b        i      s1s      s2s       sc       si
*      Total     cont   binary  integer     sos1     sos2    scont     sint
*         11       11        0        0        0        0        0        0
*  FX      0
*  
*  Nonzero counts
*      Total    const       NL      DLL
*         26       18        8        0
*
*  Solve m using NLP minimizing objvar;


Variables  objvar,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11;

Positive Variables  x2,x3,x4,x5,x6,x7,x8,x9,x10,x11;

Equations  e1,e2,e3,e4,e5,e6,e7,e8,e9,e10;


e1..  - objvar - x2 - 3*x3 =E= 0;

e2..  - x2 + x3 + x4 =E= 3;

e3..    x2 + 2*x3 + x5 =E= 12;

e4..    4*x2 - x3 + x6 =E= 12;

e5..  - x3 + x7 =E= 0;

e6.. x8*x4 =E= 0;

e7.. x9*x5 =E= 0;

e8.. x10*x6 =E= 0;

e9.. x11*x7 =E= 0;

e10..    x8 + 2*x9 - x10 - x11 =E= -1;

Model m / all /;

m.limrow=0; m.limcol=0;
m.tolproj=0.0;

$if NOT '%gams.u1%' == '' $include '%gams.u1%'

$if not set NLP $set NLP NLP
Solve m using %NLP% minimizing objvar;


Last updated: 2024-12-17 Git hash: 8eaceb91
Imprint / Privacy Policy / License: CC-BY 4.0